Data engineering and analytics: pipelines, warehousing, visualisation, and the unglamorous work of making numbers trustworthy.
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A support team asked Gemini to box product defects in customer photos - here is what 300 tickets revealed about where its coordinates can be trusted.
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A law firm needed to find 'negligence' by meaning, not keywords, while still filtering by date and department - here's the BigQuery ML query that did both.
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A telecom's support tickets started mentioning '5G outages' their schema didn't recognize. Here's how Gemini's zero-shot classification caught it.
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